Sensors Webinar | Sensor Centric-Data Intense Approaches to Manufacturing Operations from Cradle to Grave
the chairs
10th Sensors Webinar
Sensor Centric-Data Intense Approaches to Manufacturing Operations from Cradle to Grave
We are delighted to welcome you to participate in the webinar, entitled "Sensor-Centric Data-Intense Approaches to Manufacturing Operations from Cradle to Grave." The webinar will address various concepts, from developing and deploying smart sensors in your operations, to securely transferring the data generated from those sensors to the cloud for further analysis. Finally, we will introduce a world expert, who will discuss how the latest advancements in artificial intelligence (AI) and machine learning (ML), can be used to process the substantial amounts of data that your next-generation facility generates. These discussions will link the life of your data from creation/cradle to final cloud processing/grave. Furthermore, these same data might be critical for maintenance, process control, and warranty information, meaning the life of your manufacturing data extends well beyond the initial production cycle. We will wrap up with an engaging discussion about the benefits of sensor-centric data-intense manufacturing operations (and some opportunities that will necessitate pursuing them), and we will highlight and address some of the pitfalls and threats that may accompany this digital transformation.
Date: 22 September 2023
Time: 4:00 pm CEST | 10:00 am EDT | 10:00 pm CST Asia
Webinar ID: 878 8150 0308
Webinar Secretariat: journal.webinar@mdpi.com
Meet the Event Chairs
Meet Our Speakers
Dr. Vincent Paquit
Electrical and Electronics Systems Research (EESR) Division, Oak Ridge National Laboratory, Oak Ridge, USA;
Vincent Paquit is Section Head for Secure and Digital Manufacturing in the Manufacturing Science Division and Data Analytics Lead for the Manufacturing Demonstration Facility (MDF) at the Oak Ridge National Laboratory. Paquit joined ORNL in 2004 as a Research Assistant while studying for a PhD in Electrical Engineering at the University of Burgundy, France. His early research interests revolved around computer vision and image processing, such as 2D and 3D image segmentation, pattern recognition, remote sensing data interpretation, machine learning, multi- and hyper-spectral imaging, and algorithm development for GPU platforms. In recent years, he has taken on a leadership role in the development of the Data Analytics Framework for Advanced Manufacturing. This framework enhances the comprehension of manufacturing processes, enabling part qualification and certification, as well as process control and correction. Paquit's team actively contributed to the transformation of the MDF into a digital factory. This transformation involved capturing and analyzing digital threads associated with varied manufacturing technologies employed at the facility, spanning from design and modeling to simulation, material feedstock, and component fabrication and evaluation. Paquit's vision and leadership significantly influenced numerous projects and programs within ORNL, the DOE, and the DoD. With the support of the DOE Advanced Materials and Manufacturing Technologies Office (AMMTO), his work has made a substantial impact in terms of advancing scientific knowledge and innovation in the field of digital manufacturing.
Dr. Lihui Wang
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;
Lihui Wang is a Chair–Professor at the KTH Royal Institute of Technology, Sweden. His research interests include cyber–physical production systems, human–robot collaborative assembly, brain robotics, and adaptive manufacturing systems. Professor Wang has several current roles related to these interests. He is Editor-in-Chief of International Journal of Manufacturing Research, Journal of Manufacturing Systems, and Robotics and Computer-Integrated Manufacturing. He has published 10 books and authored more than 650 scientific publications. Professor Wang is also a Fellow of the Canadian Academy of Engineering (CAE), the International Academy for Production Engineering (CIRP), the Society of Manufacturing Engineers (SME), and the American Society of Mechanical Engineers (ASME). He has registered Professional Engineer status in Canada, and he formerly served as President (2020-2021) of the North American Manufacturing Research Institution of SME and Chairman (2018-2020) of the Swedish Production Academy. In 2020, he was selected as one of the 20 Most Influential Professors in Smart Manufacturing by the Society of Manufacturing Engineers.
Dr. Paulo Costa
Department of Systems Engineering and Operations Research, George Mason University, Fairfax, USA;
Paulo Costa is Interim Chair of the Department of Cyber Security Engineering and Director of the C4I and Cyber Center at George Mason University, as well as Vice President for Securing Automation and Supply Chain Security at the DOE's Cybersecurity Manufacturing Innovation Institute (CyManII). His research interests include cyber security, decision support systems, systems design and integration, multi-sensor data fusion, and probabilistic representation and reasoning. Costa has actively participated in various initiatives in the fields of cyber security of mission-critical systems, such as developing algorithms and methodologies to improve the safety and security of railways, airways, and healthcare systems. His most recent project in this field considered advanced manufacturing and supply chain security, in which he devised and coordinated multidisciplinary research teams at CyManII to develop the Cybersecurity Emissions and Energy Quantification framework (CEEQ). As Director of one of oldest and largest research centers at George Mason University, he manages multidisciplinary teams working on advanced research on mission-critical applications at different levels of security. Costa is also a former fighter pilot and has an extensive academic service record, including two tenures as President of the International Society of Information Fusion, where he currently serves as a Member of the Board of Directors.
Sponsors and Partners
Organizer
"Sensors for Machine Condition Monitoring, Diagnostics, Prognostics, and Maintenance"
Edited by Janis Terpenny, Thomas Kurfess, Vittal Prabhu and Dazhong Wu
Deadline for manuscript submissions: 25 January 2024